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Abstract Cold pools play a range of important roles in quasi-linear convective systems (QLCSs), including maintenance via the development of new convective cells as well as baroclinic generation of horizontal vorticity. Although a number of QLCS cold pools have been characterized in the literature using one or a few sensors, their variability (both internally and across a range of environments) has still not been widely studied. This gap in knowledge extends particularly to high-shear low-CAPE (HSLC) convective environments common to the cool season in the southeastern United States, where the Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign was focused. PERiLS specifically targeted environmental and storm-scale processes in QLCSs, including their cold pools. Our analysis focuses on the heterogeneity and temporal variability of cold pools across short time and spatial scales using numerous surface and sounding observations across five PERiLS QLCSs. The PERiLS cold pools are generally weaker than those previously studied in warm-season, midlatitude QLCSs, likely due to the lower CAPE and higher relative humidity values common to HSLC environments during PERiLS. Nevertheless, the distributions of most PERiLS cold pool variables at least partially overlap with those of previously studied QLCSs. The median PERiLS measurement reveals a cold pool that is ≈2.5 km deep, having a surface temperature decrease of ≈−6°C, and a peak outflow wind gust of ≈13 m s⁻¹. In the spirit of a “cold pool audit,” we present the internal and case-to-case variability of these particularly well-observed QLCSs. Significance StatementEvaporatively cooled air masses (“cold pools”) are created by quasi-linear convective systems (“QLCSs,” also called “squall lines”), and they in turn play important roles in the maintenance and structures of QLCSs. There have been relatively few direct measurements of cold pool variability, especially for the frequently severe QLCSs occurring during the cool season in the southeastern United States. Numerous surface and upper-air measurements from the recent Propagation, Evolution, and Rotation in Linear Storms (“PERiLS”) field experiment are used to document Southeastern QLCS cold pools. The PERiLS cold pools were surprisingly similar to, albeit somewhat weaker than, those found in prior studies of warm-season QLCSs in other regions. 

Abstract The first step toward eukaryotic genome duplication is loading of the replicative helicase onto chromatin. This ‘licensing’ step initiates with the recruitment of the origin recognition complex (ORC) to chromatin, which is thought to occur via ORC’s ATP-dependent DNA binding and encirclement activity. However, we have previously shown that ATP binding is dispensable for the chromatin recruitment of fly ORC, raising the question of how metazoan ORC binds chromosomes. We show here that the intrinsically disordered region (IDR) of fly Orc1 is both necessary and sufficient for recruitment of ORC to chromosomes in vivo and demonstrate that this is regulated by IDR phosphorylation. Consistently, we find that the IDR confers the ORC holocomplex with ATP-independent DNA binding activity in vitro. Using phylogenetic analysis, we make the surprising observation that metazoan Orc1 IDRs have diverged so markedly that they are unrecognizable as orthologs and yet we find that these compositionally homologous sequences are functionally conserved. Altogether, these data suggest that chromatin is recalcitrant to ORC’s ATP-dependent DNA binding activity, necessitating IDR-dependent chromatin tethering, which we propose poises ORC to opportunistically encircle nucleosome-free regions as they become available. 

Abstract MotivationProtein sequences can be broadly categorized into two classes: those which adopt stable secondary structure and fold into a domain (i.e. globular proteins), and those that do not. The sequences belonging to this latter class are conformationally heterogeneous and are described as being intrinsically disordered. Decades of investigation into the structure and function of globular proteins has resulted in a suite of computational tools that enable their sub-classification by domain type, an approach that has revolutionized how we understand and predict protein functionality. Conversely, it is unknown if sequences of disordered protein regions are subject to broadly generalizable organizational principles that would enable their sub-classification. ResultsHere, we report the development of a statistical approach that quantifies linear variance in amino acid composition across a sequence. With multiple examples, we provide evidence that intrinsically disordered regions are organized into statistically non-random modules of unique compositional bias. Modularity is observed for both low and high-complexity sequences and, in some cases, we find that modules are organized in repetitive patterns. These data demonstrate that disordered sequences are non-randomly organized into modular architectures and motivate future experiments to comprehensively classify module types and to determine the degree to which modules constitute functionally separable units analogous to the domains of globular proteins. Availability and implementationThe source code, documentation, and data to reproduce all figures are freely available at https://github.com/MWPlabUTSW/Chi-Score-Analysis.git. The analysis is also available as a Google Colab Notebook (https://colab.research.google.com/github/MWPlabUTSW/Chi-Score-Analysis/blob/main/ChiScore_Analysis.ipynb). 

Abstract Over the last decade, supercell simulations and observations with ever increasing resolution have provided new insights into the vortex-scale processes of tornado formation. This article incorporates these and other recent findings into the existing three-step model by adding an additional fourth stage. The goal is to provide an updated and clear picture of the physical processes occurring during tornadogenesis. Specifically, we emphasize the importance of the low-level wind shear and mesocyclone for tornado potential, the organization and interaction of relatively small-scale pre-tornadic vertical vorticity maxima, and the transition to a tornado-characteristic flow. Based on these insights, guiding research questions are formulated for the decade ahead. 

Abstract This study investigates whether quasi-random surface vertical vorticity is sufficient for tornadogenesis when combined with an updraft typical of tornadic supercells. The viability of this pathway could mean that a coherent process to produce well-organized surface vertical vorticity is rather unimportant. Highly idealized simulations are used to establish random noise as a possible seed for the production of tornado-like vortices (TLVs). A number of sensitivities are then examined across the simulations. The most explanatory predictor of whether a TLV will form (and how strong it will become) is the maximal value of initial surface circulation found near the updraft. Perhaps surprisingly, sufficient circulation for tornadogenesis is often present even when the surface vertical vorticity field lacks any obvious organized structure. The other key ingredient for TLV formation is confirmed to be a large vertical gradient in vertical velocity close to the ground (to promote stretching). Overall, it appears that random surface vertical vorticity is indeed sufficient for TLV formation given adequate stretching. However, it is shown that longer-wavelength noise is more likely to be associated with substantial surface circulation (because it is the areal integral of vertical vorticity). Thus, coherent vorticity sources that produce longer-wavelength structures are likely to be the most supportive of tornadogenesis. 

Abstract The national upgrade of the operational weather radar network to include polarimetric capabilities has lead to numerous studies focusing on polarimetric radar signatures commonly observed in supercells. One such signature is the horizontal separation of regions of enhanced differential reflectivity ( Z DR ) and specific differential phase ( K DP ) values due to hydrometeor size sorting. Recent observational studies have shown that the orientation of this separation tends to be more perpendicular to storm motion in supercells that produce tornadoes. Although this finding has potential operational utility, the physical relationship between this observed radar signature and tornadic potential is not known. This study uses an ensemble of supercell simulations initialized with tornadic and nontornadic environments to investigate this connection. The tendency for tornadic supercells to have a more perpendicular separation orientation was reproduced, although to a lesser degree. This difference in orientation angles was caused by stronger rearward storm-relative flow in the nontornadic supercells, leading to a rearward shift of precipitation and, therefore, the enhanced K DP region within the supercell. Further, this resulted in an unfavorable rearward shift of the negative buoyancy region, which led to an order of magnitude less baroclinic generation of circulation in the nontornadic simulations compared to tornadic simulations. 

Abstract Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity (ω_h) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, |ω_h|, and cosϕ(whereϕis the angle betweenSRFandω_h). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15 906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ω_s) in the observed profiles is |ω_h|. Furthermore, |ω_h| and |SRF| are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked toω_handSRF, while the angle between them appears to be mostly inconsequential. Significance StatementAbout three-fourths of all tornadoes are produced by rotating thunderstorms (supercells). When the part of the storm near cloud base (approximately 1 km above the ground) rotates more strongly, the chance of a tornado dramatically increases. The goal of this study is to identify the simplest characteristic(s) of the environmental wind profile that can be used to forecast the likelihood of strong cloud-base rotation. This study concludes that the most important ingredients for storm rotation are the magnitudes of the horizontal vertical wind shear between the surface and 500 m and the storm inflow wind, irrespective of their relative directions. This finding may lead to improved operational identification of environments favoring tornado formation. 

Abstract Sufficient low-level storm-relative flow is a necessary ingredient for sustained supercell thunderstorms and is connected to supercell updraft width. Assuming a supercell exists, the role of low-level storm-relative flow in regulating supercells’ low-level mesocyclone intensity is less clear. One possibility considered in this article is that storm-relative flow controls mesocyclone and tornado width via its modulation of overall updraft extent. This hypothesis relies on a previously postulated positive correspondence between updraft width, mesocyclone width, and tornado width. An alternative hypothesis is that mesocyclone characteristics are primarily regulated by horizontal streamwise vorticity irrespective of storm-relative flow. A matrix of supercell simulations was analyzed to address the aforementioned hypotheses, wherein horizontal streamwise vorticity and storm-relative flow were independently varied. Among these simulations, mesocyclone width and intensity were strongly correlated with horizontal streamwise vorticity, and comparatively weakly correlated with storm-relative flow, supporting the second hypothesis. Accompanying theory and trajectory analysis offers the physical explanation that, when storm-relative flow is large and updrafts are wide, vertically tilted streamwise vorticity is projected over a wider area but with a lesser average magnitude than when these parameters are small. These factors partially offset one another, degrading the correspondence of storm-relative flow with updraft circulation and rotational velocity, which are the mesocyclone attributes most closely tied to tornadoes. These results refute the previously purported connections between updraft width, mesocyclone width, and tornado width, and emphasize horizontal streamwise vorticity as the primary control on low-level mesocyclones in sustained supercells. Significance Statement The intensity of a supercell thunderstorm’s low-level rotation, known as the “mesocyclone,” is thought to influence tornado likelihood. Mesocyclone intensity depends on many environmental attributes that are often correlated with one another and difficult to disentangle. This study used a large body of numerical simulations to investigate the influence of the speed of low-level air entering a supercell (storm-relative flow), the horizontal spin of the ambient air entering the thunderstorm (streamwise vorticity), and the width of the storm’s updraft. Our results suggest that the rotation of the mesocyclone in supercells is primarily influenced by streamwise vorticity, with comparatively weaker connections to storm-relative flow and updraft width. These findings provide important clarification in our scientific understanding of how a storm’s environment influences the rate of rotation of its mesocyclone, and the associated tornado threat. 

This paper presents the design, implementation, and experimental evaluation of a wireless biomedical implant platform exploiting the magnetoelectric effect for wireless power and bi-directional communication. As an emerging wireless power transfer method, magnetoelectric is promising for mm-scaled bio-implants because of its superior misalignment sensitivity, high efficiency, and low tissue absorption compared to other modalities [46, 59, 60]. Utilizing the same physical mechanism for power and communication is critical for implant miniaturization, but low-power magnetoelectric uplink communication has not been achieved yet. For the first time, we design and demonstrate near-zero power magnetoelectric backscatter from the mm-sized implants by exploiting the converse magnetostriction effects. The system for demonstration consists of an 8.2-mm3 wireless implantable device and a custom portable transceiver. The implant's ASIC interfacing with the magnetoelectric transducer encodes uplink data by changing the transducer's load, resulting in resonance frequency changes for frequency-shift-keying modulation. The magnetoelectrically backscattered signal is sensed and demodulated through frequency-to-digital conversion by the external transceiver. With design optimizations in data modulation and recovery, the proposed system archives > 1-kbps data rate at the 335-kHz carrier frequency, with a communication distance greater than 2 cm and a bit error rate less than 1E-3. Further, we validate the proposed system for wireless stimulation and sensing, and conducted ex-vivo tests through a 1.5-cm porcine tissue. The proposed magnetoelectric backscatter approach provides a path towards miniaturized wireless bio-implants for advanced biomedical applications like closed-loop neuromodulation. 

Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown.